@Article{10798587.2017.1328812, AUTHOR = {Somyeh Ezdi, Tofigh Allhvirnloo}, TITLE = {Numerical Solution of Linear Regression Based on Z-Numbers by Improved Neural Network}, JOURNAL = {Intelligent Automation \& Soft Computing}, VOLUME = {24}, YEAR = {2018}, NUMBER = {1}, PAGES = {193--204}, URL = {http://www.techscience.com/iasc/v24n1/39744}, ISSN = {2326-005X}, ABSTRACT = {In this article, the researcher at first focuses on introducing a linear regression based on the Z-number. In this regression, observations are real, but the coefficients and results of observations are unknown and in the form of Z-rating. Therefore, to estimate this type of regression, we have three distinct ways depending on different conditions dominating the problem. The three methods are a combination of artificial neural networks and fuzzy generalized improvements of the technique. Moreover the method of calculating the weights of the Z-number neural network has been mentioned and the stability of neural network weights is considered. In some examples, the answer is estimated compared with the original answer.}, DOI = {10.1080/10798587.2017.1328812} }